Integrating a Partial Model into Model Free Reinforcement Learning
By Aviv Tamar, Dotan Di Castro, R. Meir. 2012
9 citations recorded by the source corpus.
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
- Sergey Levine
- Tengyu Ma
- Yuanzhi Li
- Trevor Darrell
- Aravind Rajeswaran
- Yoshua Bengio
- Pieter Abbeel
- Zeyuan Allen-Zhu
Citations in the corpus
- Algorithmic Framework for Model-based Deep Reinforcement Learning with Theoretical Guarantees (2018, background): “…Lakshmanan et al., 2015; Hinderer, 2005; Pirotta et al., 2015; 2013), or the linear parametrization of the dynamics, policy, or value function (Abbasi-Yadkori & Szepesvári, 2011; Simchowitz et al., 2018; Dean et al., 2017; Sutton et al., 2012; Tamar et al., 2012), but not much on non-linear models.”
- EPOpt: Learning Robust Neural Network Policies Using Model Ensembles (2016, methodology): “A number of methods have also been suggested to reduce sample complexity when provided with either a baseline policy [25, 26], expert demonstration [27, 28], or approximate simulator [29, 30].”